This policy brief proposes a group of twenty (G20) coordinating committee for the governance of artificial intelligence (CCGAI) to plan and coordinate on a multilateral level the mitigation of AI risks. The G20 is the appropriate regime complex for such a metagovernance mechanism, given the involvement of the largest economies and their highest political representatives. Other regime complexes and international organizations, which also focus on AI governance, tend to either lack such political power or exclude major rivalry countries. However, such inclusive centrality is necessary to counter the fragmentation of the existing cyber regime complex and effectively coordinate the mitigation of AI risks on a global level. Therefore, the G20 CCGAI is proposed to complement and strengthen polycentric governance as well as AI governance networks. CCGAI's metagovernance function is presented as a task intended to institutionalize linkages between the CCGAI and relevant actors with the G20 complex and the broader AI and cyber regime complex. While the policy brief outlines the landscape of AI risks and proposes an agenda with AI governance challenges, the focus is on the functional and organizational features of the CCGAI and how such chartered committee can foster international collaboration. Without such global coordination, AI governance risks becoming primarily an instrument of strategic competition and rivalry. An earlier and shorter version of this policy brief was included in the Think 20 (T20) communique as a recommendation to the G20 in 2020 (Jelinek Global Solutions Initiative Foundation, 2020). The T20 is a G20 engagement group that incubates and proposes policy ideas.

Twenty-first century infrastructure needs to respond to changing demographics, becoming climate neutral, resilient, and economically affordable, while remaining a driver for development and shared prosperity. However, the infrastructure sector remains one of the least innovative and digitalized, plagued by delays, cost overruns, and benefit shortfalls. The authors assessed trends and barriers in the planning and delivery of infrastructure based on secondary research, qualitative interviews with internationally leading experts, and expert workshops. The analysis concludes that the root-cause of the industry’s problems is the prevailing fragmentation of the infrastructure value chain and a lacking long-term vision for infrastructure. To help overcome these challenges, an integration of the value chain is needed. The authors propose that this could be achieved through a use-case-based, as well as vision and governance-driven creation of federated digital platforms applied to infrastructure projects and outline a concept. Digital platforms enable full-lifecycle participation and responsible governance guided by a shared infrastructure vision. This paper has contributed as policy recommendation to the Group of Twenty (G20) in 2021.

We call for a paradigm shift in engineering education. We are entering the era of the Fourth Industrial Revolution (“4IR”), accelerated by Artificial Intelligence (“AI”). Disruptive changes affect all industrial sectors and society, leading to increased uncertainty that makes it impossible to predict what lies ahead. Therefore, gradual cultural change in education is no longer an option to ease social pain. The vast majority of engineering education and training systems, which have remained largely static and underinvested for decades, are inadequate for the emerging 4IR and AI labour markets. Nevertheless, some positive developments can be observed in the reorientation of the engineering education sector. Novel approaches to engineering education are already providing distinctive, technology-enhanced, personalised, student-centred curriculum experiences within an integrated and unified education system. We need to educate engineering students for a future whose key characteristics are volatility, uncertainty, complexity and ambiguity (“VUCA”). Talent and skills gaps are expected to increase in all industries in the coming years. The authors argue for an engineering curriculum that combines timeless didactic traditions such as Socratic inquiry, mastery-based and project-based learning and first-principles thinking with novel elements, e.g., student-centred active and e-learning with a focus on case studies, as well as visualization/metaverse and gamification elements discussed in this paper, and a refocusing of engineering skills and knowledge enhanced by AI on human qualities such as creativity, empathy and dexterity. These skills strengthen engineering students’ perceptions of the world and the decisions they make as a result. This 4IR engineering curriculum will prepare engineering students to become curious engineers and excellent collaborators who navigate increasingly complex multistakeholder ecosystems.

Network effects, economies of scale, and lock-in-effects increasingly lead to a concentration of digital resources and capabilities, hindering the free and equitable development of digital entrepreneurship, new skills, and jobs, especially in small communities and their small and medium-sized enterprises (“SMEs”). To ensure the affordability and accessibility of technologies, promote digital entrepreneurship and community well-being, and protect digital rights, we propose data cooperatives as a vehicle for secure, trusted, and sovereign data exchange. In post-pandemic times, community/SME-led cooperatives can play a vital role by ensuring that supply chains to support digital commons are uninterrupted, resilient, and decentralized. Digital commons and data sovereignty provide communities with affordable and easy access to information and the ability to collectively negotiate data-related decisions. Moreover, cooperative commons (a) provide access to the infrastructure that underpins the modern economy, (b) preserve property rights, and (c) ensure that privatization and monopolization do not further erode self-determination, especially in a world increasingly mediated by AI. Thus, governance plays a significant role in accelerating communities’/SMEs’ digital transformation and addressing their challenges. Cooperatives thrive on digital governance and standards such as open trusted application programming interfaces (“APIs”) that increase the efficiency, technological capabilities, and capacities of participants and, most importantly, integrate, enable, and accelerate the digital transformation of SMEs in the overall process. This review article analyses an array of transformative use cases that underline the potential of cooperative data governance. These case studies exemplify how data and platform cooperatives, through their innovative value creation mechanisms, can elevate digital commons and value chains to a new dimension of collaboration, thereby addressing pressing societal issues. Guided by our research aim, we propose a policy framework that supports the practical implementation of digital federation platforms and data cooperatives. This policy blueprint intends to facilitate sustainable development in both the Global South and North, fostering equitable and inclusive data governance strategies.

Digital federated platforms and data cooperatives for secure, trusted and sovereign data exchange will play a central role in the construction industry of the future. With the help of platforms, cooperatives and their novel value creation, the digital transformation and the degree of organization of the construction value chain can be taken to a new level of collaboration. The goal of this research project was to develop an experimental prototype for a federated innovation data platform along with a suitable exemplary use case. The prototype is to serve the construction industry as a demonstrator for further developments and form the basis for an innovation platform. It exemplifies how an overall concept is concretely implemented along one or more use cases that address high-priority industry pain points. This concept will create a blueprint and a framework for further developments, which will then be further established in the market. The research project illuminates the perspective of various governance innovations to increase industry collaboration, productivity and capital project performance and transparency as well as the overall potential of possible platform business models. However, a comprehensive expert survey revealed that there are considerable obstacles to trust-based data exchange between the key stakeholders in the industry value network. The obstacles to cooperation are predominantly not of a technical nature, but of a competitive, predominantly trust-related nature. To overcome these obstacles and create a pre-competitive space of trust, the authors therefore propose the governance structure of a data cooperative model, which is discussed in detail in this paper.